






"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


snake_case : int     		=		logging.get_logger(__name__)

snake_case : Dict     		=		{
    """facebook/detr-resnet-50""": """https://huggingface.co/facebook/detr-resnet-50/resolve/main/config.json""",
    # See all DETR models at https://huggingface.co/models?filter=detr
}



class        UpperCamelCase__ (				a_):







    """simple docstring"""
    __UpperCAmelCase           = """detr"""
    __UpperCAmelCase           = ["""past_key_values"""]
    __UpperCAmelCase           = {
        """hidden_size""": """d_model""",
        """num_attention_heads""": """encoder_attention_heads""",
    }







    def __init__(		self :	Tuple				,    UpperCamelCase_ :	Dict=True				,    UpperCamelCase_ :	int=None				,    UpperCamelCase_ :	int=3				,    UpperCamelCase_ :	Tuple=1_0_0				,    UpperCamelCase_ :	List[str]=6				,    UpperCamelCase_ :	Union[str, Any]=2_0_4_8				,    UpperCamelCase_ :	str=8				,    UpperCamelCase_ :	Optional[int]=6				,    UpperCamelCase_ :	str=2_0_4_8				,    UpperCamelCase_ :	Union[str, Any]=8				,    UpperCamelCase_ :	Union[str, Any]=0.0				,    UpperCamelCase_ :	Tuple=0.0				,    UpperCamelCase_ :	str=True				,    UpperCamelCase_ :	Optional[Any]="relu"				,    UpperCamelCase_ :	Optional[int]=2_5_6				,    UpperCamelCase_ :	Dict=0.1				,    UpperCamelCase_ :	Union[str, Any]=0.0				,    UpperCamelCase_ :	Optional[Any]=0.0				,    UpperCamelCase_ :	int=0.02				,    UpperCamelCase_ :	List[str]=1.0				,    UpperCamelCase_ :	Optional[Any]=False				,    UpperCamelCase_ :	Dict="sine"				,    UpperCamelCase_ :	str="resnet50"				,    UpperCamelCase_ :	Tuple=True				,    UpperCamelCase_ :	str=False				,    UpperCamelCase_ :	str=1				,    UpperCamelCase_ :	List[str]=5				,    UpperCamelCase_ :	Optional[int]=2				,    UpperCamelCase_ :	Tuple=1				,    UpperCamelCase_ :	Tuple=1				,    UpperCamelCase_ :	Union[str, Any]=5				,    UpperCamelCase_ :	Dict=2				,    UpperCamelCase_ :	Union[str, Any]=0.1				,    **UpperCamelCase_ :	str				,    ):





           '''simple docstring'''

           if backbone_config is not None and use_timm_backbone:
                  raise ValueError('You can\'t specify both `backbone_config` and `use_timm_backbone`.' )

           if not use_timm_backbone:
                  if backbone_config is None:
                         logger.info('`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.' )
                         __magic_name__      				=    CONFIG_MAPPING['resnet'](out_features=['stage4'] )
                  elif isinstance(UpperCamelCase_				,    UpperCamelCase_ ):
                         __magic_name__      				=    backbone_config.get('model_type' )
                         __magic_name__      				=    CONFIG_MAPPING[backbone_model_type]
                         __magic_name__      				=    config_class.from_dict(UpperCamelCase_ )
                  # set timm attributes to None
                  __magic_name__				,  __magic_name__				,  __magic_name__      				=    None, None, None

           __magic_name__      				=    use_timm_backbone
           __magic_name__      				=    backbone_config
           __magic_name__      				=    num_channels
           __magic_name__      				=    num_queries
           __magic_name__      				=    d_model
           __magic_name__      				=    encoder_ffn_dim
           __magic_name__      				=    encoder_layers
           __magic_name__      				=    encoder_attention_heads
           __magic_name__      				=    decoder_ffn_dim
           __magic_name__      				=    decoder_layers
           __magic_name__      				=    decoder_attention_heads
           __magic_name__      				=    dropout
           __magic_name__      				=    attention_dropout
           __magic_name__      				=    activation_dropout
           __magic_name__      				=    activation_function
           __magic_name__      				=    init_std
           __magic_name__      				=    init_xavier_std
           __magic_name__      				=    encoder_layerdrop
           __magic_name__      				=    decoder_layerdrop
           __magic_name__      				=    encoder_layers
           __magic_name__      				=    auxiliary_loss
           __magic_name__      				=    position_embedding_type
           __magic_name__      				=    backbone
           __magic_name__      				=    use_pretrained_backbone
           __magic_name__      				=    dilation
           # Hungarian matcher
           __magic_name__      				=    class_cost
           __magic_name__      				=    bbox_cost
           __magic_name__      				=    giou_cost
           # Loss coefficients
           __magic_name__      				=    mask_loss_coefficient
           __magic_name__      				=    dice_loss_coefficient
           __magic_name__      				=    bbox_loss_coefficient
           __magic_name__      				=    giou_loss_coefficient
           __magic_name__      				=    eos_coefficient
           super().__init__(is_encoder_decoder=UpperCamelCase_				,    **UpperCamelCase_ )







    @property
    def 				a__			(		self :	Tuple ):





           '''simple docstring'''

           return self.encoder_attention_heads







    @property
    def 				a__			(		self :	Tuple ):





           '''simple docstring'''

           return self.d_model







    @classmethod
    def 				a__			(		cls :	Tuple				,    UpperCamelCase_ :	PretrainedConfig				,    **UpperCamelCase_ :	Tuple ):





           '''simple docstring'''

           return cls(backbone_config=UpperCamelCase_				,    **UpperCamelCase_ )







    def 				a__			(		self :	int ):





           '''simple docstring'''

           __magic_name__      				=    copy.deepcopy(self.__dict__ )
           if output["backbone_config"] is not None:
                  __magic_name__      				=    self.backbone_config.to_dict()
           __magic_name__      				=    self.__class__.model_type
           return output



class        UpperCamelCase__ (				a_):







    """simple docstring"""
    __UpperCAmelCase           = version.parse("""1.11""")







    @property
    def 				a__			(		self :	Tuple ):





           '''simple docstring'''

           return OrderedDict(
               [
                   ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
                   ('pixel_mask', {0: 'batch'}),
               ] )







    @property
    def 				a__			(		self :	Optional[int] ):





           '''simple docstring'''

           return 1e-5







    @property
    def 				a__			(		self :	List[str] ):





           '''simple docstring'''

           return 1_2







"""simple docstring"""
def 							A						(				__snake_case: int  )    ->		int:

       """simple docstring"""





       if divisor % 5 == 0 or divisor % 2 == 0:
              return 0
       __magic_name__      				=    1
       __magic_name__      				=    1
       while repunit:
              __magic_name__      				=    (1_0 * repunit + 1) % divisor
              repunit_index += 1
       return repunit_index


def 							A						(				__snake_case: int = 1_0_0_0_0_0_0  )    ->		int:

       """simple docstring"""





       __magic_name__      				=    limit - 1
       if divisor % 2 == 0:
              divisor += 1
       while least_divisible_repunit(__snake_case  ) <= limit:
              divisor += 2
       return divisor


if __name__ == "__main__":
 print(f"""{solution() = }""")